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Anti-forensics of contrast enhancement in digital images

Published: 09 September 2010 Publication History

Abstract

The blind detection of contrast enhancement in digital images has attracted much attention of the forensic analyzers. In this paper, we propose new variants of contrast enhancement operators which are undetectable by the existing contrast enhancement detectors based on the peak-gap artifacts of the pixel graylevel histogram. Local random dithering is introduced into the design of contrast enhancement mapping for removing such artifacts. Effectiveness of the proposed anti-forensic scheme is validated by experimental results on a large image database for various parameter settings. Both detectability and the resulting image quality are evaluated via comparison with the traditional contrast enhancement. The developed anti-forensic techniques could verify the reliability of existing contrast enhancement forensic tools against sophisticated attackers and serve as the targets for developing more reliable and secure forensic techniques.

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  • (2024)Image Forensics in the Encrypted DomainEntropy10.3390/e2611090026:11(900)Online publication date: 24-Oct-2024
  • (2024)Systematic Review: Anti-Forensic Computer TechniquesApplied Sciences10.3390/app1412530214:12(5302)Online publication date: 19-Jun-2024
  • (2024)Adversarial mimicry attacks against image splicing forensics: An approach for jointly hiding manipulations and creating false detectionsPattern Recognition Letters10.1016/j.patrec.2024.01.023179(73-79)Online publication date: Mar-2024
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      cover image ACM Conferences
      MM&Sec '10: Proceedings of the 12th ACM workshop on Multimedia and security
      September 2010
      264 pages
      ISBN:9781450302869
      DOI:10.1145/1854229
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 09 September 2010

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      Author Tags

      1. anti-forensics
      2. contrast enhancement
      3. digital image forensics
      4. forgery detection
      5. undetectable contrast enhancement

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      MM&Sec '10
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      MM&Sec '10: Multimedia and Security Workshop
      September 9 - 10, 2010
      Roma, Italy

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      Overall Acceptance Rate 128 of 318 submissions, 40%

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      Cited By

      View all
      • (2024)Image Forensics in the Encrypted DomainEntropy10.3390/e2611090026:11(900)Online publication date: 24-Oct-2024
      • (2024)Systematic Review: Anti-Forensic Computer TechniquesApplied Sciences10.3390/app1412530214:12(5302)Online publication date: 19-Jun-2024
      • (2024)Adversarial mimicry attacks against image splicing forensics: An approach for jointly hiding manipulations and creating false detectionsPattern Recognition Letters10.1016/j.patrec.2024.01.023179(73-79)Online publication date: Mar-2024
      • (2023)On the Security of the One-and-a-Half-Class Classifier for SPAM Feature-Based Image ForensicsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.326616818(2466-2479)Online publication date: 2023
      • (2023)An approach for anti-forensic contrast enhancement detection using grey level co-occurrence matrix and Zernike momentsInternational Journal of Information Technology10.1007/s41870-023-01191-015:3(1625-1636)Online publication date: 16-Mar-2023
      • (2023)Understanding digital image anti-forensics: an analytical reviewMultimedia Tools and Applications10.1007/s11042-023-15866-083:4(10445-10466)Online publication date: 22-Jun-2023
      • (2023)Refined GAN-Based Attack Against Image Splicing Detection and Localization AlgorithmsAdversarial Multimedia Forensics10.1007/978-3-031-49803-9_4(93-123)Online publication date: 15-Nov-2023
      • (2022)Anti-Forensic Attacks Using Generative Adversarial NetworksMultimedia Forensics10.1007/978-981-16-7621-5_17(467-490)Online publication date: 2-Apr-2022
      • (2022)Exploring the Role of Adversarial Attacks in Image Anti-forensicsComputer Vision and Image Processing10.1007/978-3-031-11349-9_47(542-551)Online publication date: 24-Jul-2022
      • (2021)Dual-Domain Fusion Convolutional Neural Network for Contrast Enhancement ForensicsEntropy10.3390/e2310131823:10(1318)Online publication date: 9-Oct-2021
      • Show More Cited By

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